Aircraft energy management and propulsion integrated system

Abstract

The invention relates to the technical field of aircrafts, in particular to an aircraft energy management and propulsion integrated system which comprises an energy management module, an aerodynamic energy capture and conversion module, a propulsion system module, a monitoring and feedback module and a safety management module. The energy management module coordinates various energy sources in the aircraft and optimizes energy distribution; the aerodynamic energy capture and conversion module captures aerodynamic energy through a micro turbine integrated on the surface of the aircraft; the propulsion system module automatically switches propulsion modes according to different stages of a flight task; the monitoring and feedback module automatically adjusts the working state of the aircraft; the safety management module detects an abnormal condition in the aircraft. According to the invention, the use of electric energy, heat energy and aerodynamic force can be dynamically adjusted, the total energy consumption is minimized, the cruising ability of the aircraft is prolonged, and the energy utilization efficiency is improved.

Description

Technical Field

[0001] The present invention relates to the field of aircraft technology, and in particular to an aircraft energy management and propulsion integrated system. Background Art

[0002] With the rapid development of modern aviation technology, the performance requirements of aircraft are getting higher and higher, especially the energy management and propulsion systems of aircraft are crucial to the overall operating efficiency and flight safety. Modern aircraft not only rely on traditional fuel propulsion systems, but also introduce a variety of new energy sources (such as electrical energy, regenerative energy, etc.) to improve energy utilization efficiency and reduce fuel consumption. At the same time, the energy requirements of aircraft in different flight phases (such as take-off, cruising, acceleration, landing, etc.) vary significantly. Therefore, how to effectively manage and allocate multiple energy sources to achieve efficient propulsion and energy utilization has become one of the important directions of aviation technology development.

[0003] Most of the current aircraft energy management and propulsion systems rely solely on fuel as the main energy source. The application of other energy sources such as electricity is limited, and the energy capture and conversion efficiency is low. In addition, existing systems often lack intelligent coordination mechanisms for multiple energy sources, resulting in the inability to flexibly adjust energy distribution in different flight phases, causing energy waste and inefficiency. In terms of propulsion systems, the traditional single propulsion mode (fuel or electric propulsion) cannot adapt to the complex needs of flight missions, and the flexibility of propulsion switching is poor. When the propulsion system fails, there is a lack of a complete automatic switching and safety management mechanism, and the stable operation of the aircraft cannot be guaranteed in time. In addition, the existing aircraft energy management system has low efficiency in energy capture and conversion when facing complex airflow conditions, and cannot dynamically optimize system performance.

[0004] The purpose of the present invention is to provide an integrated aircraft energy management and propulsion system that can dynamically adjust the energy usage of the aircraft in different flight phases, minimize fuel consumption, and improve the overall efficiency of the system. At the same time, through a complete safety management mechanism, the system can automatically switch to a backup system under abnormal conditions such as propulsion failure or energy overload to ensure the safe operation of the aircraft, thereby significantly improving the energy utilization, operating stability and endurance of the aircraft. Summary of the invention

[0005] The present invention provides an integrated aircraft energy management and propulsion system.

[0006] An integrated aircraft energy management and propulsion system includes an energy management module, an aerodynamic energy capture and conversion module, a propulsion system module, a monitoring and feedback module, and a safety management module, wherein;

[0007] The energy management module coordinates multiple energy sources within the aircraft and optimizes energy distribution, wherein the multiple energy sources include electrical energy, thermal energy, and aerodynamic energy;

[0008] The aerodynamic energy capture and conversion module utilizes the airflow kinetic energy generated by the relative motion between the aircraft and the air during flight, captures the aerodynamic energy through a micro-turbine integrated on the surface of the aircraft, and converts it into electrical energy, specifically including:

[0009] Airflow capture device: When the aircraft is flying, the kinetic energy of the airflow is captured through multiple small turbine devices distributed on the wings and fuselage;

[0010] Energy conversion device: converts the captured airflow kinetic energy into electrical energy through a power generation device, and stores the converted electrical energy in an energy storage unit or directly supplies it to the propulsion system, and adjusts the working state of the turbine according to the real-time airflow conditions;

[0011] Intelligent control unit: monitors airflow status in real time and uses optimization algorithms to adjust the rotation speed of the turbine to optimize energy capture efficiency;

[0012] The propulsion system module includes an electric propulsion unit and a fuel propulsion unit, which automatically switches the propulsion mode according to different stages of the flight mission;

[0013] The monitoring and feedback module monitors the energy capture efficiency, the energy consumption and output power of the propulsion system, and the flight parameters of the aircraft in real time, and automatically adjusts the working state of the aircraft through a feedback control mechanism;

[0014] The safety management module detects abnormal conditions in the aircraft, including energy overload, aerodynamic capture device failure or propulsion system failure, and automatically switches to a backup propulsion system when an abnormal condition is detected.

[0015] Optionally, the energy management module includes:

[0016] Real-time flight status monitoring: Real-time monitoring of the aircraft's flight parameters, including speed v, acceleration a, altitude h, and airflow intensity Q, through a variety of sensors (speed sensor, acceleration sensor, altitude sensor, airflow intensity sensor);

[0017] Current energy demand calculation: Use an energy optimization algorithm based on weight allocation to prioritize and allocate each energy source and calculate the current energy demand;

[0018] Future energy demand prediction: Based on the real-time collected flight parameters, the energy demand prediction model is used to predict the energy demand of the future flight stage;

[0019] Optimal Energy Allocation and Coordination: Dynamically optimizes energy usage from electrical, thermal and air power sources through an optimization algorithm that minimizes total energy consumption, taking into account current and future energy needs.

[0020] Optionally, the energy demand prediction model adopts a Gaussian process regression model, and the Gaussian process regression model includes:

[0021] Input features: Collect the flight parameters of the current stage as input features X t ;

[0022] Construct the covariance function (kernel function) of Gaussian process regression: use adaptive kernel width, adjust the correlation range of radial basis function (RBF) according to different flight states, and add noise kernel function to deal with measurement noise in flight state;

[0023] Calculate the predicted distribution of current energy demand: based on the input features X t and the covariance function of Gaussian process regression, using Gaussian process to predict the future energy demand distribution, the prediction result is a mean and variance, that is, the predicted energy demand and the uncertainty of the prediction;

[0024] Dynamic update of energy demand: Since the energy demand of the aircraft changes in real time with the flight status, a dynamic update mechanism is introduced to adapt to the changing flight status through recursive updates;

[0025] Obtain future energy requirements: Obtain the energy requirements for future flight phases based on the output of the Gaussian process regression model.

[0026] Optionally, the airflow capturing device comprises:

[0027] Layout of turbine devices: multiple small turbine devices are arranged on the wings and fuselage surface of the aircraft, and the small turbine devices are distributed at predetermined intervals;

[0028] Capture of airflow kinetic energy: When the aircraft is in flight, due to the relative motion between the aircraft and the surrounding air, the airflow kinetic energy is captured by a small turbine device;

[0029] Conversion of kinetic energy into mechanical energy: The airflow drives the turbine blades to rotate, converting the captured airflow kinetic energy into mechanical energy, which is then transmitted to the energy conversion unit through the shaft of the turbine system.

[0030] Optionally, the energy conversion device comprises:

[0031] Conversion of mechanical energy into electrical energy: Mechanical energy is converted into electrical energy in the energy conversion unit through a power generation device (micro generator), and the electrical energy is transmitted to the energy storage device or propulsion system of the aircraft through wires;

[0032] Storage and use of electrical energy: The converted electrical energy is directly used in the aircraft's electric propulsion system or stored in an energy storage unit;

[0033] Airflow status monitoring and turbine dynamic adjustment: The airflow intensity and direction during flight are monitored in real time through airflow sensors, and the working status of the turbine (speed, angle) is automatically adjusted based on the monitoring results.

[0034] Optionally, the intelligent control unit includes:

[0035] Real-time monitoring of airflow status: airflow sensors distributed on the surface of the aircraft can monitor the status of airflow in real time, including airflow speed, airflow direction and airflow intensity;

[0036] Turbine status data acquisition: obtain the current turbine operating status parameters, including the current rotation speed, load and inclination angle of the turbine blades;

[0037] Optimization algorithm application: Based on the real-time monitored airflow status and the current working state parameters of the turbine, the intelligent control unit starts the optimization algorithm to calculate the optimal rotation speed of the turbine;

[0038] Turbine rotation speed adjustment: Based on the calculated optimal rotation speed of the turbine, the intelligent control unit dynamically adjusts the rotation speed of the turbine.

[0039] Optionally, the optimization algorithm adopts a particle swarm optimization algorithm, and the particle swarm optimization algorithm includes:

[0040] Particle initialization: Initialize the particle swarm, each particle represents the set value of the turbine rotation speed. When the particle swarm is initialized, the airflow state (airflow speed, airflow direction, airflow intensity) and the turbine working state (rotation speed, load, inclination angle of the turbine blades) are monitored in real time and used as input parameters of the optimization process;

[0041] Fitness function calculation: According to the current airflow state (airflow speed, direction and intensity) and the working state of the turbine (load, rotation speed, blade inclination), the fitness value of each particle is calculated. The fitness value represents the efficiency of energy capture at the turbine rotation speed.

[0042] Update particle speed and position: When updating particle speed and position, refer to the changes in airflow state and turbine state;

[0043] Update individual historical optimal and global optimal: The fitness value of each particle is calculated based on the current airflow state and turbine state;

[0044] Iteration termination condition: Through continuous iteration, until the upper limit of the iteration number is reached or the change of the global optimal solution is less than the preset threshold, finally, the turbine rotation speed corresponding to the global optimal position will be taken as the optimal solution.

[0045] Optionally, the propulsion system module includes:

[0046] Mission phase identification: real-time monitoring of flight mission status parameters, including flight altitude, speed, mission time and mission phase, and identification of the current mission phase of the aircraft, including take-off, acceleration, cruising or landing;

[0047] Propulsion mode selection: Select the corresponding propulsion mode according to the current mission stage. In the high thrust demand stage (take-off, acceleration, climb), select the fuel propulsion unit. In the low thrust demand stage (cruise, landing), switch to the electric propulsion unit first.

[0048] Propulsion system switching execution: The switching of the propulsion system is executed through automatic control logic. The switching process achieves seamless connection by adjusting the power output of the fuel propulsion unit and the electric propulsion unit.

[0049] Optionally, the monitoring and feedback module includes:

[0050] Energy capture efficiency monitoring: Real-time monitoring of the energy capture efficiency of small turbine devices;

[0051] Propulsion system energy consumption and output power monitoring: By collecting the energy usage of the fuel propulsion unit and the electric propulsion unit, the energy consumption (including fuel and electricity) and propulsion output power of the propulsion system are monitored in real time;

[0052] Flight parameter monitoring: real-time monitoring of aircraft flight parameters, including flight speed, altitude, acceleration, and airflow intensity;

[0053] Application of feedback control mechanism: compare the monitored energy capture efficiency, propulsion system energy consumption and output power, and flight parameters with the preset optimization target. If the monitored value is lower than the preset optimization target, the working state of the aircraft is automatically adjusted, including:

[0054] Automatically optimize the turbine's rotation speed based on energy capture efficiency;

[0055] Automatically adjust propulsion power output according to the energy consumption and output power of the propulsion system to optimize the use of fuel or electricity;

[0056] Automatically adjust the flight attitude and propulsion mode according to the aircraft's flight parameters (speed, altitude, acceleration and airflow intensity).

[0057] Optionally, the security management module includes:

[0058] Real-time monitoring of abnormal conditions: Real-time monitoring of abnormal conditions of the aircraft, including energy overload (energy demand or consumption is detected to exceed the specified safety range, resulting in equipment overload), aerodynamic capture device failure (the turbine device cannot operate normally or the capture efficiency decreases beyond the safety threshold), and propulsion system failure (insufficient thrust or complete failure of the fuel propulsion unit or electric propulsion unit);

[0059] Automatic switchover to backup propulsion system and energy distribution: Automatic emergency switchover operations upon identification of energy overload, propulsion system failure or aerodynamic capture device failure, including:

[0060] Failure of the fuel propulsion unit: Automatically switch to the electric propulsion unit;

[0061] If the electric propulsion unit fails: switch to the fuel propulsion unit;

[0062] Aerodynamic capture device failure: When an aerodynamic capture device failure affects propulsion, the power output of the propulsion system is adjusted in real time;

[0063] Energy overload handling: Optimizes energy distribution by reducing the power output of the propulsion system when an energy overload is detected.

[0064] Beneficial effects of the present invention:

[0065] The present invention coordinates multiple energy sources such as electrical energy, thermal energy and aerodynamics through the energy management module, thereby achieving efficient energy utilization of the aircraft in different flight stages such as take-off, cruising, acceleration and landing. Through the energy capture and conversion module, the kinetic energy of the airflow during the flight can be effectively captured, converted into electrical energy and reasonably distributed to the propulsion system and energy storage unit. At the same time, based on the prediction of energy demand and the optimal energy allocation algorithm, the use of electrical energy, thermal energy and aerodynamics can be dynamically adjusted to minimize total energy consumption, extend the endurance of the aircraft and improve energy utilization efficiency.

[0066] The present invention, through an intelligent control unit and a particle swarm optimization algorithm, can automatically switch between fuel propulsion and electric propulsion according to different stages of the flight mission, thereby minimizing fuel consumption and improving flight efficiency. The intelligent control unit dynamically adjusts the rotation speed of the turbine by real-time monitoring of the airflow state and the turbine working state, ensuring the best energy capture efficiency under complex airflow conditions. At the same time, the propulsion system switches smoothly, realizing efficient and intelligent propulsion management, so that the aircraft can flexibly adapt to mission requirements in a complex flight environment.

[0067] The present invention can monitor abnormal conditions of the aircraft in real time through the safety management module, such as energy overload, failure of the aerodynamic capture device or failure of the propulsion system. When the system detects an abnormal condition, it can automatically switch to the backup propulsion system and ensure the smooth operation of the aircraft by adjusting the propulsion power and energy distribution to avoid damage caused by overload of the equipment. At the same time, through the setting of preset optimization goals and safety thresholds, the system can respond to abnormal conditions in a timely manner to ensure the safe operation of the aircraft under complex flight conditions, thereby greatly improving the stability and reliability of the system. BRIEF DESCRIPTION OF THE DRAWINGS

[0068] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings in the following description are only for the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0069] Figure 1 A schematic diagram of system function modules according to an embodiment of the present invention;

[0070] Figure 2 Schematic diagram of an aerodynamic energy capture and conversion module according to an embodiment of the present invention. DETAILED DESCRIPTION

[0071] The present invention is described in detail below in conjunction with the accompanying drawings and specific embodiments. At the same time, it is explained here that in order to make the embodiments more detailed, the following embodiments are the best and preferred embodiments, and those skilled in the art may also adopt other alternatives to implement some known technologies; and the accompanying drawings are only for more specific description of the embodiments, and are not intended to specifically limit the present invention.

[0072] It should be noted that the references to "one embodiment", "an embodiment", "an exemplary embodiment", "some embodiments" and the like in the specification indicate that the embodiments described may include specific features, structures or characteristics, but not every embodiment may include the specific features, structures or characteristics. In addition, when a specific feature, structure or characteristic is described in conjunction with an embodiment, it should be within the knowledge of a person skilled in the art to implement such feature, structure or characteristic in conjunction with other embodiments (whether or not explicitly described).

[0073] In general, a term can be understood, at least in part, from its use in context. For example, depending, at least in part, on the context, the term "one or more" as used herein can be used to describe any feature, structure, or characteristic in the singular sense, or can be used to describe a combination of features, structures, or characteristics in the plural sense. Additionally, the term "based on" can be understood as not necessarily intended to convey an exclusive set of factors, but can instead, depending, at least in part, on the context, allow for the presence of other factors that are not necessarily explicitly described.

[0074] like Figure 1-Figure 2 As shown, an integrated system for energy management and propulsion of an aircraft includes an energy management module, an aerodynamic energy capture and conversion module, a propulsion system module, a monitoring and feedback module, and a safety management module, wherein;

[0075] The energy management module coordinates and optimizes the energy distribution of multiple energy sources inside the aircraft, including electrical energy, thermal energy and aerodynamic energy, to ensure efficient energy utilization during different flight phases such as takeoff, cruising, acceleration and landing;

[0076] The aerodynamic energy capture and conversion module uses the airflow kinetic energy generated by the relative motion between the aircraft and the air during flight, captures the aerodynamic energy through a micro-turbine integrated on the surface of the aircraft, and converts it into electrical energy. Specifically, it includes:

[0077] Airflow capture device: When the aircraft is flying, the kinetic energy of the airflow is captured through multiple small turbine devices distributed on the wings and fuselage;

[0078] Energy conversion device: converts the captured airflow kinetic energy into electrical energy through a power generation device, and stores the converted electrical energy in an energy storage unit or directly supplies it to the propulsion system, and adjusts the working state of the turbine according to the real-time airflow conditions to ensure the maximum efficiency of energy capture and conversion;

[0079] Intelligent control unit: monitors airflow status in real time and uses optimization algorithms to adjust the rotation speed of the turbine to optimize energy capture efficiency and ensure the best energy conversion effect under different flight speeds and airflow conditions;

[0080] The propulsion system module includes an electric propulsion unit and a fuel propulsion unit, which automatically switches the propulsion mode according to the different stages of the flight mission to reduce fuel consumption and improve the overall efficiency of the system;

[0081] The monitoring and feedback module monitors the energy capture efficiency, energy consumption and output power of the propulsion system, and flight parameters of the aircraft in real time, and automatically adjusts the working state of the aircraft through the feedback control mechanism;

[0082] The safety management module detects abnormal conditions in the aircraft, including energy overload, aerodynamic capture device failure or propulsion system failure, and automatically switches to the backup propulsion system when an abnormal condition is detected to ensure the safe operation of the aircraft;

[0083] Through the above content, multiple energy management and propulsion modules are integrated to build an efficient and intelligent aircraft energy management and propulsion integrated system, which can achieve efficient coordination and utilization of multiple energy forms in various stages of the aircraft. Through aerodynamic energy capture and conversion, automatic switching of the propulsion system, real-time monitoring and feedback control, and safety management, energy distribution is optimized, fuel consumption is reduced, and the overall energy efficiency and reliability of the system are improved, ensuring the safe and efficient operation of the aircraft under complex flight conditions.

[0084] The energy management module includes:

[0085] Real-time flight status monitoring: Real-time monitoring of the aircraft's flight parameters, including speed v, acceleration a, altitude h, and airflow intensity Q, through a variety of sensors (speed sensor, acceleration sensor, altitude sensor, airflow intensity sensor);

[0086] Calculation of current energy demand: An energy optimization algorithm based on weight distribution is used to assign priorities to each energy source and calculate the current energy demand, which is expressed as:

[0087] E current =w1E elec +w2E thermal +w3E aero ;

[0088] Among them, E current It represents the total energy demand of the aircraft in the current flight phase, E elec is the available energy of the electrical energy source, E thermal Indicates the energy provided by the thermal energy source, E aero represents the energy provided by the aerodynamic source, w1, w2, w3 are the dynamic weights of each energy source, satisfying w1+w2+w3=1;

[0089] Future energy demand prediction: Based on the real-time collected flight parameters, the energy demand prediction model is used to predict the energy demand of the future flight stage;

[0090] Optimal energy allocation and coordination: Dynamically optimize the use of electrical, thermal and air power sources through an optimization algorithm that minimizes total energy consumption, taking into account current and future energy needs, including:

[0091] (1) Constructing the objective function of total energy consumption: The goal of the system is to minimize the total energy consumption, taking into account the use of electrical energy, thermal energy, and aerodynamic energy, expressed as:

[0092] minC total =w1C elec +w2C thermal +w3C aero ;

[0093] Among them, C total is the total energy consumption of the aircraft, C elec is the power consumption, indicating the power consumption from batteries, regenerative braking, etc., C thermal is the heat energy consumption, which indicates the use of waste heat from the engine or propulsion system, C aero is the aerodynamic energy consumption, which indicates the energy consumption of the airflow kinetic energy capture system. w1, w2, and w3 are the dynamic weights of electrical energy, thermal energy, and aerodynamic energy, respectively, reflecting the relative contribution of each energy source at the current stage.

[0094] (2) Energy allocation constraints: To ensure that energy allocation meets the needs of the aircraft, the following constraints must be met, including:

[0095] 1) Energy demand constraint: The sum of current and future energy demands should be equal to the total energy allocated, expressed as:

[0096] E current +E future =w1E elec +w2E thermal +w3E aero ;

[0097] Among them, E current is the total energy demand of the aircraft in the current flight phase, E future is the energy demand for the predicted future flight phase, E elec is the available electrical energy, E thermal is the available thermal energy, E aero is the available energy obtained through the aerodynamic capture system;

[0098] 2) Weight constraint: The sum of the weights of the energy sources must satisfy w1+w2+w3=1;

[0099] 3) Energy upper limit constraint: The use of each energy source cannot exceed its maximum available value, expressed as:

[0100] E elec ≤E elec,max ,E thermal ≤E thermal,max ,E aero ≤E aero,max ;

[0101] Among them, E elec,max 、E thermal,max、E aero,max are the maximum available values ​​of electrical energy, thermal energy and aerodynamic energy at the current stage, respectively;

[0102] (3) Optimization algorithm for optimal energy allocation: By minimizing the total energy consumption and satisfying the above constraints, the system uses a linear programming optimization algorithm to dynamically allocate energy to solve the optimal values ​​of weights w1, w2, and w3, expressed as:

[0103] minC total =w1C elec +w2C thermal +w3C aero ;

[0104] subject to w1+w2+w3=1 and E current +E future =w1E elec +w2E thermal +w3E aero ;

[0105] Under the premise of meeting the above constraints, the system adjusts the weights of various energy sources to ensure that electrical energy, thermal energy and aerodynamic energy are reasonably distributed to minimize total energy consumption;

[0106] Through the above content, the flight status is monitored in real time, and the use of electrical energy, thermal energy and aerodynamic energy is dynamically optimized in combination with current and future energy needs. On the premise of meeting energy needs and system constraints, the total energy consumption is minimized to ensure the efficiency and rationality of energy distribution. It can adapt to the changes of the aircraft in different flight phases, improve energy utilization, extend the flight time of the aircraft, reduce overall energy consumption, and thus improve the operating efficiency and safety of the aircraft.

[0107] The energy demand prediction model adopts the Gaussian process regression model, which includes:

[0108] Input features: Collect the flight parameters of the current stage as input features X t , expressed as:

[0109] X t =[v t ,a t ,h t ,Q t ];

[0110] Among them, v t is the current flight speed, a t is the current flight acceleration, h t is the current flight altitude, Q t is the current airflow strength;

[0111] Construct the covariance function (kernel function) of Gaussian process regression: use adaptive kernel width, adjust the correlation range of radial basis function (RBF) according to different flight states, and add noise kernel function to deal with measurement noise in flight state, expressed as:

[0112]

[0113] Among them, k(X i ,X j ) are two input data points X i and X j The covariance (or similarity) between them is used to construct the kernel function of the Gaussian process, X i and X j are different flight state inputs, D is the flight state dimension (speed, acceleration, altitude, airflow intensity), l d is the adaptive kernel width of each dimension, indicating the influence range of the feature, is the signal variance, indicating the magnitude of the prediction, is the noise variance, dealing with the noise in the flight state measurements, δ ij It is Kronecker delta, which is used to deal with noise in the same state;

[0114] Calculate the predicted distribution of current energy demand: based on the input features X t As well as the covariance function of Gaussian process regression, the Gaussian process is used to predict the future energy demand distribution. The prediction result is a mean and variance, that is, the predicted energy demand and the uncertainty of the prediction, expressed as:

[0115]

[0116] Among them, μ(X t ) is the predicted mean of current energy demand, σ 2 (X t ) is the uncertainty (variance) of the forecast, K(X,X) is the covariance matrix between the historical data X, K(X t ,X) is the current input X t The covariance vector between the historical data X, Y is the historical energy demand data, k(X t ,X t ) is the current input X t The covariance with itself, K(X,X t ) is the historical data X and the current input X t The covariance relationship between

[0117] Dynamic update of energy demand: Since the energy demand of the aircraft changes in real time with the flight status, a dynamic update mechanism is introduced to adapt to the changing flight status through recursive updates, which is expressed as:

[0118]

[0119]

[0120] Among them, K new is the updated covariance matrix, indicating that at the new observation point X t+1 The updated covariance matrix after introduction, K(X t+1 ,X) is the covariance vector between the new observation point and the historical data, K(X,X t+1 ) is the covariance vector between historical data and new observation points, k(X t+1 ,X t+1 ) is the new observation point X t+1 Its own covariance, μ(X t+1 ) is the new observation point X t+1 The predicted mean, K(X t+1 ,X new ) is the covariance vector between the new observation point and the updated data set, X new is the updated input data set, that is, the historical data plus the new observation points, Y new is the updated historical energy demand data;

[0121] Obtaining future energy demand: According to the output of the Gaussian process regression model, the energy demand for the future flight phase is obtained, which is expressed as:

[0122] E future =μ(X t+1 );

[0123] Among them, E future Energy requirements for predicted future flight phases;

[0124] Through the above content, the introduction of adaptive kernel functions and dynamic update mechanisms can accurately capture the changes in the energy demand of the aircraft under different flight states and predict future energy demand in real time. Gaussian process regression can not only provide the predicted mean of energy demand, but also quantify the prediction uncertainty, making the system more stable and accurate when facing complex nonlinear flight environments. Dynamic updates ensure that the model obtains the latest flight status information at any time, thereby optimizing energy management and effectively improving the energy utilization efficiency and operational safety of the aircraft.

[0125] The airflow capture device includes:

[0126] Layout of turbine devices: Multiple small turbine devices are arranged on the wings and fuselage of the aircraft. The small turbine devices are distributed at predetermined intervals to ensure that the airflow kinetic energy generated by the relative movement with the air during flight can be effectively captured at different parts of the aircraft;

[0127] Capture of airflow kinetic energy: When the aircraft is in flight, due to the relative motion between the aircraft and the surrounding air, the airflow kinetic energy is captured by a small turbine device;

[0128] Conversion of kinetic energy into mechanical energy: The airflow drives the turbine blades to rotate, converting the captured airflow kinetic energy into mechanical energy, which is then transferred to the energy conversion unit through the shaft of the turbine system;

[0129] Through the above content, it is possible to fully utilize the kinetic energy of the airflow generated by the aircraft during flight, efficiently capture and convert it into usable mechanical energy through a small turbine device, and then further convert it into electrical energy for the propulsion or other systems of the aircraft. This not only reduces dependence on traditional fuels during flight and improves the efficiency of energy use, but also ensures maximum energy capture under different flight conditions by dynamically adjusting the working state of the turbine. In addition, the turbine device is reasonably distributed and can adapt to changes in airflow in different flight phases, thereby enhancing the overall energy efficiency and endurance of the aircraft.

[0130] The energy conversion device includes:

[0131] Conversion of mechanical energy into electrical energy: Mechanical energy is converted into electrical energy in the energy conversion unit through a power generation device (micro generator), and the electrical energy is transmitted to the energy storage device or propulsion system of the aircraft through wires;

[0132] Storage and use of electrical energy: The converted electrical energy is directly used in the aircraft's electric propulsion system or stored in an energy storage unit to meet the energy needs of other systems during subsequent flight;

[0133] Airflow status monitoring and turbine dynamic adjustment: The airflow intensity and direction during flight are monitored in real time through airflow sensors. Based on the monitoring results, the turbine's working status (speed, angle) is automatically adjusted to ensure the capture and conversion efficiency of airflow kinetic energy is optimized under different flight conditions.

[0134] Through the above content, the kinetic energy of the airflow captured by the aircraft during flight can be efficiently converted into electrical energy, and the use and storage of electrical energy can be intelligently allocated. By real-time monitoring of the airflow status and automatically adjusting the working status of the turbine, the energy capture and conversion efficiency can be dynamically optimized according to different flight conditions, ensuring maximum energy utilization under various airflow conditions. This not only improves the aircraft's endurance, but also reduces dependence on traditional fuels, improving the system's energy efficiency and environmental performance.

[0135] The intelligent control unit includes:

[0136] Real-time monitoring of airflow status: airflow sensors distributed on the surface of the aircraft can monitor the status of airflow in real time, including airflow speed, airflow direction and airflow intensity;

[0137] Turbine status data acquisition: obtain the current turbine operating status parameters, including the current rotation speed, load and inclination angle of the turbine blades;

[0138] Optimization algorithm application: Based on the real-time monitored airflow status and the current working state parameters of the turbine, the intelligent control unit starts the optimization algorithm to calculate the optimal rotation speed of the turbine to maximize the energy capture efficiency;

[0139] Turbine rotation speed adjustment: Based on the calculated optimal rotation speed of the turbine, the intelligent control unit dynamically adjusts the turbine rotation speed to ensure that the turbine achieves the best energy capture efficiency under the current airflow conditions;

[0140] Through the above content, the system ensures accurate perception of the flight environment. With the help of optimization algorithms, the intelligent control unit can dynamically adjust the rotation speed of the turbine to adapt to different airflow conditions and maximize the energy capture efficiency. It not only improves the energy utilization efficiency, but also reduces energy loss, ensuring the stability and endurance of the aircraft in complex airflow environments, thereby greatly improving the overall performance of the aircraft and the reliability of its operation.

[0141] The optimization algorithm adopts the particle swarm optimization algorithm, which includes:

[0142] Particle initialization: Initialize the particle swarm, each particle represents the rotation speed setting value of the turbine. When the particle swarm is initialized, the airflow state (airflow speed, airflow direction, airflow intensity) and the turbine working state (rotation speed, load, inclination angle of the turbine blades) are monitored in real time and used as input parameters of the optimization process, expressed as:

[0143]

[0144] in, represents the turbine rotation speed of the i-th particle in the 0th generation (initial moment) in the particle swarm optimization algorithm, x min ,x max are the minimum and maximum values ​​of the turbine rotation speed (determined according to the mechanical constraints), represents the velocity of the i-th particle in the 0th generation (initial moment) in the particle swarm optimization algorithm, q min ,q max are the minimum and maximum values ​​of the velocity, i.e., the velocity variation range of the particle;

[0145] Fitness function calculation: According to the current airflow state (airflow speed, direction and intensity) and the working state of the turbine (load, rotation speed, blade inclination), the fitness value of each particle is calculated. The fitness value represents the efficiency of energy capture at the turbine rotation speed, which is expressed as:

[0146]

[0147] in, represents the fitness value of the ith particle in the tth generation, represents the efficiency of energy capture at the current turbine rotation speed, represents the turbine energy capture efficiency of the i-th particle, which depends on the airflow velocity q, the turbine rotation speed The blade inclination angle θ i And the load L i , E airflow (q) is the kinetic energy of the airflow;

[0148]

[0149] Where ρ is the air density, which is approximately 1.225 kg / m 3 (at sea level and standard conditions), A is the force area of ​​the turbine, that is, the force cross-sectional area of ​​the turbine blades and the airflow, and v is the airflow velocity, which indicates the flow velocity of the airflow in the current environment;

[0150] Update particle speed and position: When updating particle speed and position, refer to the changes in airflow state and turbine state to ensure that the system reaches the optimal rotation speed under different flight conditions, expressed as:

[0151]

[0152] in, is the speed of the ith particle in the t+1th generation, that is, the rate of change of the rotation speed of the next generation of particles. ω is the inertia weight, which controls the speed update of the particle and balances the ability of local search and global search. A larger ω value will increase the particle's dependence on the current speed, while a smaller value will prompt the particle to approach the optimal solution faster. c1 is the individual learning factor, which measures the degree to which the particle approaches its own historical optimal position. c2 is the group learning factor, which measures the degree to which the particle approaches the group's historical optimal position. r1 and r2 are random numbers in the range of [0,1], which are used to increase the randomness of the search and prevent particles from falling into the local optimal solution. is the historical optimal position of the i-th particle, indicating the best turbine rotation speed found by the particle in previous generations, g t is the global optimal position of the current population, indicating the best turbine rotation speed found in all generations among all particles, is the rotation speed of the ith particle in the t+1th generation, indicating the updated turbine rotation speed setting value. The particle position is updated based on the current speed and the previous generation position;

[0153] Update individual historical optimal and global optimal: The fitness value of each particle is calculated according to the current airflow state and turbine state, expressed as:

[0154]

[0155]

[0156] in, is the historical optimal position of the ith particle in the t+1th generation, g t+1 is the updated global optimal position, which represents the rotation speed setting value of the optimal particle in the current group;

[0157] Iteration termination condition: through continuous iteration, until the upper limit of the number of iterations is reached or the change of the global optimal solution is less than the preset threshold, finally, the turbine rotation speed corresponding to the global optimal position will be taken as the optimal solution;

[0158] The preset thresholds are set based on the turbine energy capture efficiency requirements and the actual energy requirements of the aircraft, including:

[0159] (1) Determine the target energy capture efficiency: Determine the target energy capture efficiency E of the turbine system based on the specific energy management requirements of the aircraft. targrt , E targrt It can be obtained through experiments, design requirements, or estimates of the energy requirements of the aircraft;

[0160] (2) Define the change in the global optimal solution: In each iteration of particle swarm optimization, calculate the change Δg of the global optimal solution between the current iteration and the previous iteration t , which indicates the improvement of the global optimal solution in energy capture efficiency, and is expressed as:

[0161] Δg t =|Fitness(g t )-Fitness(g t-1 )|;

[0162] Among them, Fitness(g t ) is the fitness value (energy capture efficiency) of the t-th generation global optimal solution, Fitness(g t -1 ) is the fitness value of the global optimal solution of the t-1th generation;

[0163] (3) Setting the global optimal solution change threshold: According to the target energy capture efficiency E targrtThe accuracy requirement is set, and the threshold ∈ of the global optimal solution change is set. The threshold is set to a certain percentage of the target energy capture efficiency to ensure that the iteration is stopped when the accuracy is sufficient, which is expressed as:

[0164] ∈=α×E target ;

[0165] Among them, ∈ is the threshold value of the global optimal solution change, indicating the minimum change of the fitness value, α is the proportional constant, indicating the change ratio of the energy capture efficiency (for example, 1% means α = 0.01), E target is the target energy capture efficiency, the energy capture efficiency value expected by the system;

[0166] (4) Iteration termination condition judgment: After each iteration, compare the change Δg of the global optimal solution t And the set threshold ∈, if the change of the global optimal solution is less than the threshold, the algorithm is considered to have converged and the iteration is stopped, otherwise the optimization continues;

[0167] (5) The adaptability of adjusting the threshold: According to the actual energy demand of the aircraft and the changes in the airflow environment, the threshold ∈ is appropriately adjusted. If the flight conditions change dramatically (such as large fluctuations in airflow speed), the threshold can be lowered to increase the optimization accuracy. If the energy capture efficiency is close enough to the target value and the system is stable, the threshold can be increased to reduce the computational overhead.

[0168] Through the above content, it is possible to dynamically find the optimal solution for energy capture efficiency under complex airflow conditions. The airflow state (speed, direction, intensity) and turbine working state (rotation speed, load, blade inclination) are combined to ensure real-time optimization of the turbine working efficiency at different flight stages. The particle swarm optimization algorithm can not only converge to the global optimal solution quickly, but also intelligently terminate the iteration after achieving the optimal energy capture efficiency by setting the global optimal solution change threshold, thereby reducing computational overhead, improving the energy utilization efficiency and operational stability of the aircraft, and enabling the aircraft to achieve optimal energy management and propulsion performance in a complex and changing environment.

[0169] The propulsion system module includes:

[0170] Mission phase identification: real-time monitoring of flight mission status parameters, including flight altitude, speed, mission time and mission phase, and identification of the current mission phase of the aircraft, including take-off, acceleration, cruising or landing;

[0171] Propulsion mode selection: Select the corresponding propulsion mode according to the current mission stage. In the high thrust demand stage (take-off, acceleration, climb), select the fuel propulsion unit to provide strong power. In the low thrust demand stage (cruise, landing), switch to the electric propulsion unit first to reduce fuel consumption and improve energy utilization efficiency.

[0172] Propulsion system switching execution: The switching of the propulsion system is executed through automatic control logic. The switching process achieves seamless connection by adjusting the power output of the fuel propulsion unit and the electric propulsion unit. For example, when switching from fuel propulsion to electric propulsion, the output power of the fuel system is gradually reduced and the output power of the electric propulsion unit is increased to ensure a smooth transition of thrust;

[0173] Through the above content, energy utilization can be dynamically optimized according to thrust requirements. In the take-off, acceleration and climbing phases with high thrust requirements, the fuel propulsion unit provides strong power, while in low thrust phases such as cruising and landing, the electric propulsion unit effectively reduces fuel consumption and carbon emissions, and improves overall energy efficiency. The system's automatic switching mechanism ensures a smooth transition of the propulsion process, and at the same time, continuous adjustments are made through real-time monitoring of flight parameters to ensure efficient and safe propulsion management of the aircraft in complex environments.

[0174] The monitoring and feedback modules include:

[0175] Energy capture efficiency monitoring: Real-time monitoring of the energy capture efficiency of small turbine devices;

[0176] Propulsion system energy consumption and output power monitoring: By collecting the energy usage of the fuel propulsion unit and the electric propulsion unit, the energy consumption (including fuel and electricity) and propulsion output power of the propulsion system are monitored in real time;

[0177] Flight parameter monitoring: real-time monitoring of aircraft flight parameters, including flight speed, altitude, acceleration, and airflow intensity;

[0178] Application of feedback control mechanism: compare the monitored energy capture efficiency, propulsion system energy consumption and output power, and flight parameters with the preset optimization target. If the monitored value is lower than the preset optimization target, the working state of the aircraft is automatically adjusted, including:

[0179] Automatically optimize the turbine's rotation speed based on energy capture efficiency;

[0180] Automatically adjust propulsion power output according to the energy consumption and output power of the propulsion system to optimize the use of fuel or electricity;

[0181] Automatically adjust flight attitude and propulsion mode according to the aircraft's flight parameters (speed, altitude, acceleration and airflow intensity) to ensure optimal energy utilization and stable flight;

[0182] The preset optimization goals include:

[0183] (1) Energy capture efficiency target setting: The energy capture efficiency optimization target is set according to the current airflow conditions and the design parameters of the turbine device. The target is expressed as the ratio of the actual energy capture efficiency of the turbine to the theoretical maximum capture efficiency, expressed as:

[0184] η target =η max ×β;

[0185] Among them, η target is the target value of energy capture efficiency, η max is the maximum energy capture efficiency that can be achieved theoretically under the current airflow conditions, β is an empirical coefficient, less than 1, and is set based on factors such as actual turbine performance and airflow fluctuations to ensure stable system operation;

[0186] (2) Propulsion system energy consumption target setting: The optimization target of the propulsion system is set as the maximum acceptable energy consumption value (including fuel and electrical energy consumption) of the aircraft at a certain stage. This target usually depends on the requirements of the flight mission and the system energy reserve, and is expressed as:

[0187] M target =M max ×γ;

[0188] Among them, M target To propel the energy consumption target of the system, M max is the maximum energy reserve available to the system at the current stage, γ is the mission coefficient, which reflects the tolerance to energy consumption in the current flight stage (for example, the energy consumption target in the cruise stage is lower than that in the take-off or climb stage);

[0189] (3) Flight parameter optimization target setting: The flight parameters (speed, altitude, acceleration, and airflow intensity) of the aircraft are set according to the flight mission and aircraft performance. The target values ​​of speed and altitude are determined by optimizing the efficiency and safety of the flight mission, expressed as:

[0190]

[0191] Among them, v target is the target value of the speed, which depends on the maximum value of the speed v max and the minimum value v min The middle value of h ensures that the aircraft maintains the best speed during stable flight. target For the target value of height, set the appropriate height range based on the task requirements;

[0192] Through the above content, it is possible to fully grasp the energy usage and flight status of the aircraft, and timely adjust the turbine rotation speed, propulsion power output and flight attitude through the feedback control mechanism. This real-time optimization capability ensures that the aircraft can operate efficiently under various flight conditions, achieves optimal energy utilization and efficient management of the propulsion system. At the same time, by comparing with the preset optimization targets, the system can quickly respond to changes in the flight mission, automatically adjust the working status, improve the aircraft's endurance and operational safety, thereby improving overall flight efficiency and reducing energy consumption.

[0193] The security management module includes:

[0194] Real-time monitoring of abnormal conditions: Real-time monitoring of abnormal conditions of the aircraft, including energy overload (energy demand or consumption is detected to exceed the specified safety range, resulting in equipment overload), aerodynamic capture device failure (the turbine device cannot operate normally or the capture efficiency decreases beyond the safety threshold), and propulsion system failure (insufficient thrust or complete failure of the fuel propulsion unit or electric propulsion unit);

[0195] Automatic switchover to backup propulsion system and energy distribution: Automatic emergency switchover operations upon identification of energy overload, propulsion system failure or aerodynamic capture device failure, including:

[0196] Failure of the fuel propulsion unit: Automatically switch to the electric propulsion unit to ensure that the aircraft continues to propel normally;

[0197] Failure of the electric propulsion unit: switch to the fuel propulsion unit to maintain the normal propulsion capability of the aircraft;

[0198] Aerodynamic capture device failure: When an aerodynamic capture device failure affects propulsion, the power output of the propulsion system is adjusted in real time to mitigate the impact of the failure;

[0199] Energy overload processing: When energy overload is detected, the power output of the propulsion system is reduced to optimize energy distribution, prevent equipment from overloading, and protect key aircraft equipment from damage;

[0200] The safety threshold is based on the standard range of energy capture efficiency, combined with historical data and equipment limit settings, expressed as:

[0201] η threshold =η max ×(1-δ);

[0202] Among them, η threshold is the safety threshold of energy capture efficiency, η maxis the maximum energy capture efficiency of the turbine under ideal conditions, obtained through testing or equipment design specifications, δ is the safety margin (safety factor), which indicates the range of energy capture efficiency drop allowed by the system, and its value range is 0<δ<1. This value is determined according to the design requirements of the system and the airflow fluctuation, and is between 5% and 15%;

[0203] Through the above content, abnormal situations such as energy overload, propulsion system failure or reduced energy capture efficiency can be detected quickly to avoid equipment overload operation. In the event of a failure, it can automatically switch to the backup propulsion system and ensure that the aircraft continues to operate smoothly through intelligent energy distribution and propulsion power adjustment. This not only improves the stability and reliability of the system and reduces the risk of flight interruption, but also protects the aircraft's key equipment by promptly handling potential problems, extending equipment life and enhancing flight safety.

[0204] The present invention covers any substitution, modification, equivalent method and scheme made on the essence and scope of the present invention. In order to make the public have a thorough understanding of the present invention, specific details are described in detail in the following preferred embodiments of the present invention, but those skilled in the art can fully understand the present invention without the description of these details. In addition, in order to avoid unnecessary confusion about the essence of the present invention, well-known methods, processes, procedures, components and circuits are not described in detail.

[0205] The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principle of the present invention. These improvements and modifications should also be regarded as the scope of protection of the present invention.

Claims

1. An integrated aircraft energy management and propulsion system, characterized in that: It includes energy management module, aerodynamic energy capture and conversion module, propulsion system module, monitoring and feedback module and safety management module, among which; The energy management module coordinates multiple energy sources within the aircraft and optimizes energy distribution, wherein the multiple energy sources include electrical energy, thermal energy, and aerodynamic energy; The aerodynamic energy capture and conversion module utilizes the airflow kinetic energy generated by the relative motion between the aircraft and the air during flight, captures the aerodynamic energy through a micro-turbine integrated on the surface of the aircraft, and converts it into electrical energy, specifically including: Airflow capture device: When the aircraft is flying, the kinetic energy of the airflow is captured through multiple small turbine devices distributed on the wings and fuselage; Energy conversion device: converts the captured airflow kinetic energy into electrical energy through a power generation device, and stores the converted electrical energy in an energy storage unit or directly supplies it to the propulsion system, and adjusts the working state of the turbine according to the real-time airflow conditions; Intelligent control unit: monitors airflow status in real time and uses optimization algorithms to adjust the rotation speed of the turbine to optimize energy capture efficiency; The propulsion system module includes an electric propulsion unit and a fuel propulsion unit, which automatically switches the propulsion mode according to different stages of the flight mission; The monitoring and feedback module monitors the energy capture efficiency, the energy consumption and output power of the propulsion system, and the flight parameters of the aircraft in real time, and automatically adjusts the working state of the aircraft through a feedback control mechanism; The safety management module detects abnormal conditions in the aircraft, including energy overload, aerodynamic capture device failure or propulsion system failure, and automatically switches to a backup propulsion system when an abnormal condition is detected.

2. An integrated aircraft energy management and propulsion system according to claim 1, characterized in that: The energy management module comprises: Real-time flight status monitoring: Real-time monitoring of aircraft flight parameters, including speed v, acceleration a, altitude h, and airflow intensity Q, through a variety of sensors; Current energy demand calculation: Use an energy optimization algorithm based on weight allocation to prioritize and allocate each energy source and calculate the current energy demand; Future energy demand prediction: Based on the real-time collected flight parameters, the energy demand prediction model is used to predict the energy demand of the future flight stage; Optimal Energy Allocation and Coordination: Dynamically optimizes energy usage from electrical, thermal and air power sources through an optimization algorithm that minimizes total energy consumption, taking into account current and future energy needs.

3. An integrated aircraft energy management and propulsion system according to claim 2, characterized in that: The energy demand prediction model adopts a Gaussian process regression model, and the Gaussian process regression model includes: Input features: Collect the flight parameters of the current stage as input features X t ; Construct the covariance function of Gaussian process regression: use adaptive kernel width to adjust the correlation range of radial basis function according to different flight states, and add noise kernel function to deal with measurement noise in flight state; Calculate the predicted distribution of current energy demand: based on the input features X t and the covariance function of Gaussian process regression, using Gaussian process to predict the future energy demand distribution, the prediction result is a mean and variance, that is, the predicted energy demand and the uncertainty of the prediction; Dynamic update of energy demand: Since the energy demand of the aircraft changes in real time with the flight status, a dynamic update mechanism is introduced to adapt to the changing flight status through recursive updates; Obtain future energy requirements: Obtain the energy requirements for future flight phases based on the output of the Gaussian process regression model.

4. An integrated aircraft energy management and propulsion system according to claim 3, characterized in that: The airflow capture device comprises: Layout of turbine devices: multiple small turbine devices are arranged on the wings and fuselage surface of the aircraft, and the small turbine devices are distributed at predetermined intervals; Capture of airflow kinetic energy: When the aircraft is in flight, due to the relative motion between the aircraft and the surrounding air, the airflow kinetic energy is captured by a small turbine device; Conversion of kinetic energy into mechanical energy: The airflow drives the turbine blades to rotate, converting the captured airflow kinetic energy into mechanical energy, which is then transferred to the energy conversion unit through the shaft of the turbine system.

5. An integrated aircraft energy management and propulsion system according to claim 4, characterized in that: The energy conversion device comprises: Conversion of mechanical energy into electrical energy: Mechanical energy is converted into electrical energy in the energy conversion unit through a power generation device, and the electrical energy is transmitted to the energy storage device or propulsion system of the aircraft through wires; Storage and use of electrical energy: The converted electrical energy is directly used in the aircraft's electric propulsion system or stored in an energy storage unit; Airflow status monitoring and turbine dynamic adjustment: The airflow intensity and direction during flight are monitored in real time through airflow sensors, and the working status of the turbine is automatically adjusted based on the monitoring results.

6. An integrated aircraft energy management and propulsion system according to claim 5, characterized in that: The intelligent control unit comprises: Real-time monitoring of airflow status: airflow sensors distributed on the surface of the aircraft can monitor the status of airflow in real time, including airflow speed, airflow direction and airflow intensity; Turbine status data acquisition: obtain the current turbine working status parameters, including the current rotation speed, load and inclination angle of the turbine blades; Optimization algorithm application: Based on the real-time monitored airflow status and the current working state parameters of the turbine, the intelligent control unit starts the optimization algorithm to calculate the optimal rotation speed of the turbine; Turbine rotation speed adjustment: Based on the calculated optimal rotation speed of the turbine, the intelligent control unit dynamically adjusts the rotation speed of the turbine.

7. An integrated aircraft energy management and propulsion system according to claim 6, characterized in that: The optimization algorithm adopts a particle swarm optimization algorithm, and the particle swarm optimization algorithm includes: Particle initialization: Initialize the particle swarm, each particle represents the rotation speed setting value of the turbine. When the particle swarm is initialized, the airflow state and the turbine working state are monitored in real time and used as input parameters of the optimization process; Fitness function calculation: According to the current airflow state and the working state of the turbine, the fitness value of each particle is calculated. The fitness value represents the efficiency of energy capture at the turbine rotation speed. Update particle speed and position: When updating particle speed and position, refer to the changes in airflow state and turbine state; Update individual historical optimal and global optimal: The fitness value of each particle is calculated based on the current airflow state and turbine state; Iteration termination condition: Through continuous iteration, until the upper limit of the iteration number is reached or the change of the global optimal solution is less than the preset threshold, finally, the turbine rotation speed corresponding to the global optimal position will be taken as the optimal solution.

8. An integrated aircraft energy management and propulsion system according to claim 7, characterized in that: The propulsion system module includes: Mission phase identification: real-time monitoring of flight mission status parameters, including flight altitude, speed, mission time and mission phase, and identification of the current mission phase of the aircraft, including take-off, acceleration, cruising or landing; Propulsion mode selection: Select the corresponding propulsion mode according to the current mission stage. In the stage of high thrust demand, select the fuel propulsion unit, and in the stage of low thrust demand, switch to the electric propulsion unit first; Propulsion system switching execution: The switching of the propulsion system is executed through automatic control logic. The switching process achieves seamless connection by adjusting the power output of the fuel propulsion unit and the electric propulsion unit.

9. An integrated aircraft energy management and propulsion system according to claim 8, characterized in that: The monitoring and feedback module includes: Energy capture efficiency monitoring: Real-time monitoring of the energy capture efficiency of small turbine devices; Propulsion system energy consumption and output power monitoring: By collecting the energy usage of the fuel propulsion unit and the electric propulsion unit, the energy consumption and propulsion output power of the propulsion system can be monitored in real time; Flight parameter monitoring: real-time monitoring of aircraft flight parameters, including flight speed, altitude, acceleration, and airflow intensity; Application of feedback control mechanism: compare the monitored energy capture efficiency, propulsion system energy consumption and output power, and flight parameters with the preset optimization target. If the monitored value is lower than the preset optimization target, the working state of the aircraft is automatically adjusted, including: Automatically optimize the turbine's rotation speed based on energy capture efficiency; Automatically adjust propulsion power output according to the energy consumption and output power of the propulsion system to optimize the use of fuel or electricity; Automatically adjust the flight attitude and propulsion mode according to the flight parameters of the aircraft.

10. The integrated aircraft energy management and propulsion system according to claim 1, characterized in that: The security management module includes: Real-time monitoring of abnormal conditions: Real-time monitoring of abnormal conditions of the aircraft, including energy overload, aerodynamic capture device failure, and propulsion system failure; Automatic switchover to backup propulsion system and energy distribution: Automatic emergency switchover operations upon identification of energy overload, propulsion system failure or aerodynamic capture device failure, including: Failure of the fuel propulsion unit: Automatically switch to the electric propulsion unit; If the electric propulsion unit fails: switch to the fuel propulsion unit; Aerodynamic capture device failure: When an aerodynamic capture device failure affects propulsion, the power output of the propulsion system is adjusted in real time; Energy overload handling: Optimizes energy distribution by reducing the power output of the propulsion system when an energy overload is detected.

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